ASReview: Active learning for Systematic Reviews

ASReview is a project to accelerate the process of systematic reviewing. It is written in Python, and uses deep learning to predict which papers should be most likely included in the review. Our software is designed to accelerate the step of screening abstracts and titles with a minimum of papers to be read by a human with no or very few false negatives.

ASReview software consists of a user friendly front-end (ASReview LAB) and a powerful command line interface. The command line interface is to measure the performance of the active learning models on the results of fully labeled systematic reviews.

The source code is freely available at GitHub.

Indices and tables

Citation

The preprint ArXiv:2006.12166 can be used to cite this project.

van de Schoot, Rens, et al. “ASReview: Open Source Software for Efficient and
Transparent Active Learning for Systematic Reviews.” ArXiv:2006.12166 [Cs],
June 2020. arXiv.org, http://arxiv.org/abs/2006.12166.

For citing the software, please refer to the specific release of the ASReview software on Zenodo DOI. The menu on the right can be used to find the citation format of prevalence.